AxonDiameter

Processing for spiral data can be started running scripts/process_spiral.sh #IN_FILE.

Preprocessing

1. Denoising (MRtrix3: "dwidenoise") preferably on complex data

2. Convert to magnitude data ("nifti2mag.py")

3. EPI:

   • TOPUP (FSL)
   • Eddy (FSL)

4. Spiral

   • Motion correction (Eddy)

5. Gradient nonlinearity correction (is essential due to high b-values/strong gradients)

   • GradientDistortionUnwarp.sh (needs https://github.com/Washington-University/gradunwarp)
   • includes b-vector correction (gradient nonlinearity correction leads to different b-values/b-vectors in different voxels)
   • Bammer, R., et al., (2003), "Analysis and generalized correction of the effect of spatial gradient field distortions in diffusion‐weighted imaging"

6. Spherical harmonic decomposition to get spherical average per shell & per voxel (MRtrix3: amp2sh)

   • correct for Rician noise bias

7. Divide the 0th order spherical harmonic by $\sqrt{4\pi}$ to get the powder average

   • Afzali, et al. "Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques"

Requirements

• MRtrix3
• FSL
• gradunwarp (included submodule)
• AxonRadiusMapping (included submodule)
• Python (incl. Numpy, Nibabel)